Estimation of Bayesian Item Response Models
The general form of a Bayesian item response model consists of a probability model for the responses, prior distributions for the model parameters, and possibly prior distributions for the hyperparameters. An overview of Bayesian procedures for simultaneous estimation is given in which MCMC estimation methods are emphasized. Interest is focused on simultaneous estimation of marginal posterior densities of item and person parameters.
KeywordsItem Parameter European Social Survey Augmented Data Discrimination Parameter Item Response Model
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